Gunay Murat, Shim Mun-Bo, Shimada Kenji
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Int J Med Robot. 2007 Dec;3(4):323-35. doi: 10.1002/rcs.162.
Three-dimensional (3D) bone shapes need to be created for visualization and pre-operative surgery planning. Conventionally such shape data is extracted from volumetric data sets, obtained by three-dimensional sensors, such as computerized tomography (CT) and magnetic resonance imaging (MRI). This conventional method is highly labor intensive and time consuming.
This paper presents a cost- and time-effective computational method for generating a 3D bone shape from multiple X-ray images. Starting with a predefined 3D template bone shape that is clinically normal and scaled to an average size, our method scales and deforms the template shape until the deformed shape gives an image similar to an input X-ray image when projected onto a two-dimensional (2D) plane. The hierarchical freeform deformation method is used to scale and deform the template bone. The problem of finding the 3D shape of the bond is reduced to a sequence of optimization problems. The objective of this optimization is to minimize the error between the input X-ray image and the projected image of the deformed template shape. The sequential quadratic programming (SQP) is used to solve this multi-dimentional optimization problem.
The proposed X-ray image-based shape reconstruction is more computationally efficient, cost-effective and portable compared to the conventional CT- or MRI-based methods. Within a couple of minutes with a standard personal computer, the proposed method generates a 3D bone shape that is sufficiently accurate for many applications, such as (a) making a 3D physical mock-up for training and (b) importing into, and using in, a computer-aided planning system for orthopedic surgery, including bone distraction and open/closed wedge osteotomy.
Because the proposed method requires only a small number of X-ray images and a minimum input from the user, the method can serve as a cost- and time-effective 3D bone shape reconstruction method for various medical applications.
为了进行可视化和术前手术规划,需要创建三维(3D)骨骼形状。传统上,此类形状数据是从通过三维传感器(如计算机断层扫描(CT)和磁共振成像(MRI))获得的体积数据集中提取的。这种传统方法劳动强度大且耗时。
本文提出了一种经济高效且省时的计算方法,用于从多个X射线图像生成3D骨骼形状。从临床正常且缩放至平均尺寸的预定义3D模板骨骼形状开始,我们的方法对模板形状进行缩放和变形,直到变形后的形状在投影到二维(2D)平面时给出与输入X射线图像相似的图像。使用分层自由形式变形方法对模板骨骼进行缩放和变形。寻找骨骼3D形状的问题被简化为一系列优化问题。此优化的目标是最小化输入X射线图像与变形模板形状的投影图像之间的误差。使用序列二次规划(SQP)来解决此多维优化问题。
与传统的基于CT或MRI的方法相比,所提出的基于X射线图像的形状重建在计算上更高效、经济且便于携带。使用标准个人计算机在几分钟内,所提出的方法就能生成对于许多应用来说足够精确的3D骨骼形状,例如(a)制作用于训练的3D实物模型,以及(b)导入并用于骨科手术的计算机辅助规划系统,包括骨延长和开放/闭合楔形截骨术。
由于所提出的方法仅需要少量X射线图像且用户输入最少,该方法可作为一种经济高效的3D骨骼形状重建方法,用于各种医疗应用。